The Customer

Teen Parent Connection (TPC) is a nonprofit social services organization in the western suburbs of Chicago, Illinois.  TPC helps prevent teenage pregnancy through a variety of educational programs and ensures teenage parents and their children get the care and support they need.  Over 10,000 middle and high school students in DuPage and surrounding counties participate in TPC’s prevention programs each year.  For more information on TPC visit www.teenparentconnection.org.

According to UNICEF, the United States has the highest teen pregnancy rate among OECD countries.  The Center for Disease Control says about one-third of girls get pregnant before the age of 20, and Teenpregnancy.org states there are about 750,000 teen pregnancies annually.  Healthcommunities.com says about 13% of U.S. births involve teen mothers and about 25% of teenage girls who give birth have another baby within 2 years.

Why does this matter?  Because raising children can be stressful and demanding, for parents and their communities.  Healthcommunities.com and Livestrong.com say teenage mothers are more likely to drop out of high school, with about one-third of teen mothers obtaining a high school diploma, and are more likely to be and remain single parents.  Healthcommunities.com also says the estimated annual cost of teen pregnancies is close to $7 billion in lost tax revenues, public assistance, child health care, foster care, and involvement with the criminal justice system.

The Solution

The Board President and Executive Director knew they needed to increase both the number and quality of prospective candidates to ensure the board had the capabilities the organization needed to succeed.  They reached out to The Taproot Foundation, an organization that serves nonprofits by connecting them with experienced professionals who provide their services pro-bono, and were introduced to CorDell Larkin, the principal and founder of CorDell & Company, who assembled a team of pro-bono consultants to assist TPC with its recruitment needs.

To ensure the board achieved both its performance and recruitment objectives, the consultants had to identify and implement appropriate measures of candidate quality and identify a larger pool of potential candidates.  Not doing so could result in a recruitment strategy that identified large pools of candidates at the expense of the very capabilities the board needed to improve its performance, and increased time and cost to screen and interview unqualified candidates.  To ensure the recruitment strategy was properly targeted at the needed capabilities, the consultants followed a structured recruitment planning process (see figure below), including analyzing the organization’s current and future plans to grow and serve its customer base, analyzing current board member capabilities to identify and prioritize any gaps, analyzing the local market for talent and trends, analyzing TPC’s branding and messaging, and then developing detailed job descriptions, a strategic recruitment plan, candidate assessment tools, and metrics to measure the plan’s success.

How it Was Implemented

To identify the future capabilities the board needed to possess, the consultants interviewed a majority of the current board members, TPC’s senior staff, executives from other high performing nonprofit organizations, and researched nonprofit board of directors best practices.  As a result, it was recommended that the board change its organizational structure, to six standing committees from three, so that the board could better focus on delivering the key services most needed by the organization.  While this would increase the Board’s recruitment workload, and it delayed implementation of the recruiting strategy, it was viewed as a necessary step to ensure future recruitment efforts were properly allocated and aligned with the organization’s greatest talent needs.

To identify any gaps between current and future capabilities, all the knowledge, skills, and abilities (KSA) the board needed to possess were defined.  A self-assessment survey was created (see example below) and completed by all current board members, and the data was compiled and analyzed.  The survey also gathered information on various organizations current board members were affiliated with and the amount of time they had available for volunteer activities and where they allocated it.  Information on organizational affiliations proved very useful in development of the recruitment strategy, as a number of the board members had connections to organizations identified as priority targets for sourcing candidates!

Then, the local market was analyzed to identify organizations likely to possess large quantities of the needed KSA, and to assess the organization’s brand messaging against other local nonprofits for attractiveness to prospective board candidates.  The consultants recommended a new communication strategy focused on all the community benefits board members enable TPC to deliver and emphasizing a personal communication approach, along with a recruitment strategy focusing on sourcing candidates from specific health care, government, corporate, education, and social organizations with the KSA needed to close the identified gaps.  The recruitment process was clearly defined, and roles and responsibilities were documented for each person involved in the process, along with decision criteria, a candidate self-assessment, and a structured interview guide (see example at right).  The consultants also developed a simple candidate tracking mechanism and metrics, such as percent of target organizations penetrated, number of qualified candidates identified, and number of candidates nominated, so TPC could periodically measure the effectiveness of the plan and its execution.

The Conclusion

Recruitment and selection for TPC’s board is now based entirely on candidate quality and will drive enhanced organizational performance.  The board has specific sourcing targets, a personalized communications strategy, and a streamlined recruitment process to identify, recruit and select high quality board members.  To be nominated board candidates must close specific KSA gaps and improve the performance of the board, and the organization now has a structured, annual process for assessing current board member competencies to identify any future gaps.

About The Taproot Foundation

Taproot’s mission is to lead, mobilize, and engage professionals in pro-bono service that drives social change.  Since 2001, Taproot Foundation has worked to engage the nation’s millions of business professionals in pro-bono services both through award-winning programs and by partnering with companies to develop corporate pro-bono programs.  One day, Taproot envisions all organizations with promising solutions will be equipped to successfully take on urgent social challenges.  For more information on Taproot visit www.taprootfoundation.org.

About CorDell & Company

Founded in 2006, CorDell & Company is a human resource consulting firm that helps organizations with human resources strategy, learning and development, leadership and management assessment, human resource effectiveness, performance measurement and management, talent acquisition, and engagement and retention.  Accuracy, Effectiveness, Honesty, Insightfulness, and Making a Difference are our core values.  Helping companies get more from their people, and helping people get more from their work, is our core purpose.  For more information on CorDell & Company visit www.cordellandcompany.com.

Download a PDF copy of this case.

If you would like help with your recruitment or performance improvement initiatives email CorDell & Company at info (at) cordellandcompany (dot) com or call +1 312-952-7342.

To determine which company is the best manager of human capital among major biotech companies CorDell & Company analyzed sales per employee, cash flow per employee, and total number of employees at Amgen, Biogen, Celgene, Genzyme, and Gilead between 2005 and 2009.

The average sales per employee (SE) for the five companies included in this study was $832,719, and the average compound annual growth rate (CAGR) for SE was approximately 8 percent. Gilead had the highest average SE at $1,412,320, almost twice the average SE of every other company in this study, and the highest CAGR for SE at 14.27 percent.  The average cash flow per employee (CFE) for these five companies was $309,125, and the average CAGR for CFE was approximately 18 percent.  Gilead had the highest average CFE at $578,718, however Celgene had the highest CAGR for CFE at 64.28 percent.  The average TNE for these five companies was 7,324, and the average CAGR for TNE was approximately 14 percent.  Celgene grew the fastest, almost tripling the size of its workforce, while Gilead doubled its workforce.

The data suggests Gilead’s workforce is the most productive, and when compared to Amgen, Biogen, Celgene, and Genzyme it is able to acquire better talent, develop better talent, or both.  Investors, however, appear to favor Celgene.  Its stock price was up approximately 319 percent over this period, while Gilead’s stock price was up approximately 147 percent and Amgen’s, Genzyme’s, and Biogen’s stock prices were down approximately 12, 16, and 20 percent respectively.  Over this period the Dow Jones Industrial Average was down approximately 2% and the S&P 500 was down approximately 8%.

CorDell & Company recommends tracking these workforce productivity metrics as part of organizational performance management efforts to identify macro level changes in human capital productivity and to assess the impact of changes in human resource management practices within an organization.  For more detailed information on how each of these organizations performs on these measures, request a copy of the research paper at http://www.cordellandcompany.com/hcpa-biotech.html.

About CorDell & Company

Founded in 2006, CorDell & Company is a human capital management consulting firm that specializes in improving organizational profits and performance by identifying, acquiring, motivating, retaining, and developing talent.

Selection Criteria

To be included in this study a company must be publicly traded with at least USD 10 billion in software revenues in fiscal year 2009 and disclose software revenues, total revenues, cash flow from operations, and total number of employees for each of the fiscal years included in the study.

Method of Analysis

Using sales per employee (SE), operating cash flow per employee (OCFE), and total number of employees (TNE) we analyze and quantify the productivity of each organizations’ workforce.  To measure SE we divide annual revenues by TNE, and to measure OCFE we divide annual net cash flow from operations by TNE.  When comparing two or more organizations with fiscal years that end at different times of the calendar year we adjust comparisons to compare as many of the same calendar months as possible.  The equations for this analysis are as follows;

Annual Revenues / TNE = SE
Annual Net Cash Flow From Operations / TNE = OCFE

Results

The average annual SE for all companies included in this study was $365,135, which is significantly skewed by Microsoft’s extremely high average annual SE.  Microsoft (MSFT) had the highest average annual SE at $643,075.  International Business Machines (IBM), Oracle (ORCL), and SAP AG (SAP) had an average annual SE of $257,810, $257,111, and $310,541 respectively.  ORCL had the highest compound annual growth rate (CAGR) in SE at 1.08 percent, while IBM, MSFT, and SAP’s CAGR for SE was -3.52, -.93, .94 percent respectively.    MSFT clearly had the most productive human capital when it comes to top line productivity, and produces 200% more than its next closest competitor in SE.  Assuming MSFT is able to capture a significant portion of revenues as profits, and can maintain a positive employer brand, it should be able to offer financial rewards to its employees that exceed those of its competitors and capture a large portion of the high quality workers within this industry.

The average annual OCFE for all companies included in this study was $105,505.  MSFT had the highest average annual OCFE at $228,509, while IBM, ORCL, and SAP had an average annual OCFE of $45,687, $82,893, and $64,933 respectively.  MSFT was the only company to have a negative CAGR for OCFE at -6.88 percent.  IBM, ORCL, and SAP had CAGRs for OCFE of 3.48, 6.09, and 11.63 percent respectively.  Even more surprising is ORCLs OCFE, which at $82,893 is 28 percent greater than SAPs OCFE and 81 percent greater than IBMs OCFE.  ORCLs SE was only 83% of SAPs SE and roughly the same as IBMs SE.

MSFT clearly had the most productive workforce when it came to generating cash flows, but it appears to be less productive over time.  ORCL had the second most productive workforce in terms of generating cash flows, and it appears to be more productive over time.  This suggests ORCL is able to acquire workers that are more productive than its average worker, improve average performance of current workers, or both.

The average annual TNE for all the companies include in this study was 141,578.  IBM had the highest average annual TNE at 373,912, while MSFT, ORCL, and SAP had average annual TNE of 79,000, 68,582, and 43,819 respectively.  ORCL had the highest CAGR in TNE at 16.38 percent, which is significant when you consider that ORCL had a below average but fast growing SE, an above average OCFE, and improved OCFE almost every year.  This suggests ORCL is the best of these companies at talent management.

While IBM grew its TNE at the slowest rate it actually added more workers to its workforce than any of these companies during this period.  This is significant when you consider that IBM also improved OCFE, but confusing when you consider IBM’s SE dropped during this period.  Taken together these data suggest IBM may face external, non-workforce related pricing competition or a lack of innovative, customer focused talent in product development and sales.

Surprisingly, MSFT was one of the fastest growing companies among this group with a CAGR for TNE of 11.12 percent.  However, with a declining SE and OCFE this suggests MSFT is unable to acquire workers that are equal to or higher performing than its existing workers or its workers become less productive the longer they are employed by the company.

SAP was the only company to decrease TNE in 2009 from 2008 levels, which may account for the significant increase in OCFE SAP experience in 2009 from 2008 levels.  If this is true, it suggests SAP has done a good job over the past year eliminating lower performing workers, but it also suggests SAP may have trouble ramping up as the economy improves as most of its gains in employee productivity came from eliminating low performers as opposed to adding or developing higher performers.

Conclusion

MSFT’s workforce was significantly more productive than the workforces of IBM, Oracle, and SAP.  However, MSFT’s declines in SE and OCFE suggest it is unable to acquire workers that perform equal to or higher than its current workers or its workers become less productive the longer they are employed at MSFT.  ORCL’s consistent improvements in SE and OCFE while simultaneously growing its workforce suggest it is the best manager of talent amongst these companies.  Not surprisingly, ORCL’s stock outperformed IBM, MSFT, and SAP during this period.  As shown in the graph below, between 2005 and 2009 ORCL’s stock was up 80 percent, while the stock prices of IBM, MSFT, and SAP were up 34, 13, and 6 percent respectively. IBM’s workforce appears good at improving operating efficiency but lacking in ability to drive sales growth, and while SAP appears to have done a good job eliminating lower performing workers it may not be prepared for an economic recovery.

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The first step in calculating the ROI for a learning and development program is to define the financial value of the behavioral change your customer desires.  To do this you must clearly define the business results your customer is getting that are a concern and quantify how the customer would like those business results to change.  The difference between the desired and current business results equals the financial value of solving this problem.  If the financial or management information system does not capture data on the business results that concerns the customer, then arrange for a pre and post measurement process, agree to an acceptable timeframe for that measurement, and include the cost of the measurement in the overall cost of the training project.  In an ideal world the business results the customer is concerned about will be easily linked to operating profits, revenues, or costs, but in some cases it won’t be that easy.  For instance, a change is sales win ratio can be easily translated to revenues by multiplying the average number of sales opportunities by the change in sales win ratio by the average deal size and then by the number of sales representatives.  The equation would look something like this;

Average number of sales opportunities X (new sales win ratio – old sales win ratio) X average deal size X number of sales representatives

A change in customer service scores effects customer retention and customer retention effects customer lifetime value, which is expressed in financial terms, so a desired change in behavior that drives improvements in customer service scores could be linked to an increase in customer lifetime value.  On the surface a change in something like the product pipeline might seem easy, but in practice it is a bit difficult because there is usually disagreement about the magnitude of the affect of intermediate measures, like number of patents filed, ideas generated, and product life times on things like average profit per product. In the case where you can’t get agreement on the affect of intermediate measures on sales, profits, or costs we recommend you skip the ROI calculation and instead use whatever financial value the customer assigns to the changes they desire.  If you take this approach you still need to make sure you have a pre and post training measurement in place to determine how effective the training was at making the desired change.

Once you have determined the financial value of the change the customer seeks we recommend you investigate to ensure you are fixing the most likely cause of the problem, and to ensure that there are no barriers to the desired behavior change.  Start by investigating changes associated with the industry, customers, and competition, to rule out factors external to the company as the cause of the poor business results.  If external factors are the likely causes of the problem, training solutions, if they are appropriate responses to these changes, can be significantly different.  Once external factors are eliminated as likely causes, investigate internal factors associated with people, process, and technology.  If the problem is linked to process or technology then training on current processes and technologies might be the best solution.  If no recent changes have been made in the customer’s technologies or processes then the problem is likely a deficiency of knowledge, skills, or abilities, and you want to make sure that any behavioral change resulting from training will not be negatively affected by current processes nor technologies.

Next you want to estimate the cost of each training solution you are considering.  The most important thing here is to capture the often unforeseen costs like training staff time invested in planning and administration and leaners time away from work.  Additionally, several organizations today offer seminars, mentorship, or coaching programs staffed by company employees and often times forget to include the time away from work for these people.  In an ideal world you will capture 100 percent of the costs associated with a program, but in reality it is probably good enough if you capture 90 percent or more.  You don’t have to be 100 percent accurate on this, but if you fail to do it you are highly likely to underestimate the costs of training programs and make poor investment decisions.

Now comes the hard part.  You have to estimate the portion of the target population you think will change its behavior, or the average behavioral change per person, as a result of the training.  This is why measuring and tracking pre and post training is so critical.  Over time this information can really help you understand what your workforce is capable of learning and improve the accuracy of future training investments.  If you have not done this before you can analyze three to four prior training programs and compare before and after performance review ratings for those who participated in the training program.  If you don’t have or can’t get this information we recommend you interview a few managers and get their opinion on the effects of past training programs.

Now you have all the information you need to estimate the ROI of a future training program.  It should look something like this;

(((financial value of the change the customer seeks X the portion of the target population who’s behavior changes) – the cost of the training program) / the cost of the training program) X 100

Here is a sales force training example to illustrate this.  In this case the company’s current win ratio is 15 percent and the sales VP wants to push that to 18 percent.  The companies current average deal size is $5,000, they have 10 sales representatives, and each sales representative gets an average of 300 qualified selling opportunities per year.  The equation to calculate the financial value of the change the sales VP wants is;

300 X (.18 – .15) X $5,000 X 10 = $450,000

The training options to consider are A) two day training with a cost of $4,500 per person, B) one day training with a cost of $2,500 per person, and C) an online course with a cost of $500 per person.  Given the company’s experience they estimate the portion of the training population that will change its behavior from these training options at 30 percent, 20 percent, and five percent respectively.  The equations to calculate the ROI of these training options are;

((($450,000 X .30) – ($4,500 X 10)) / ($4,500 X 10)) X 100 = 200%
((($450,000 X .20) – ($2,500 X 10)) / ($2,500 X 10)) X 100 = 260%
((($450,000 X .05) – ($500 X 10)) / ($500 X 10)) X 100 = 350%

While option A is estimated to produce the largest absolute lift in sales, based on this ROI calculation, the investment with the best return is option C.  Why go through this exercise?  Following these steps to calculate the ROI of learning and development programs forces you to align training investments with your customers business strategy and gives the customer the ability to evaluate this type of investment against other investments like software upgrades, process reengineering, and marketing campaigns.

If you are currently seeking training and development solutions and would like to speak with someone who can help you through the process you can email CorDell & Company at info (AT) cordellandcompany (DOT) com or call +1 312 952 7342.

About CorDell & Company

Founded in 2006, CorDell & Company is a human capital management consulting firm that specializes in improving profits and performance for both large global and small local companies by identifying, acquiring, motivating, retaining, and developing talent.

You can request a PDF of this “How To Guide” online at http://cordellandcompany.com/calculate-roi-training-development.html.

For more insights into human capital management visit the Executive’s Guide to Human Capital Blog.

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To determine who’s winning the “war for talent” among Network Equipment Manufacturers, CorDell & Company compared human capital productivity at Alcatel-Lucent (ALU), Cisco (CSCO), Ericsson (ERIC), Juniper (JNPR), and Motorola (MOT) on a number of workforce productivity measures for fiscal years 2005 to 2009.

MOT had the highest average sales per employee (SE) at $524,998, although CSCO recently overtook it as the leader in this area.  CSCO’s human capital generated the highest average operating income per employee (OIE) at $145,554, the best average operating margin (OM) at 25.13%, and the best average operating cash flow per employee (OCFE) at $170,645.  This was achieved while growing its workforce by 70%, strengthening the belief that CSCO is winning the war for talent among Network Equipment Manufacturers.  The overall average annual SE was $413,332; the overall average annual OM was 13.75%; and the overall average annual OCFE was $77,189, all of which trended downward over this period.

In addition, CSCO achieved the best stock performance during this period.  The company’s stock price was up around 23%, while ALU, ERIC, JNPR, and MOT were down around -79%, -42%, -2%, and -55% respectively.  Over this period the Dow Jones Industrial Average was down around -2% and the S&P 500 was down around -8%.

The average annual total number of employees (TNE) for all the companies included in this study was 53,958.  Every company increased TNE during this period except MOT, which saw a decline in TNE of -23.19%.  Both JNPR and CSCO increased TNE by around 70%, impressive considering both companies saw a faster decline in SE than OIE.  This suggests that they were able to both add and develop more productive talent over this time.  Also impressive is ERIC’s increase in TNE by almost 50% while OCFE stayed about the same, suggesting that ERIC found talent that is equally productive to the human capital it already had and that is operations are set up to ensure a certain level of productivity from all talent.  ALU’s increase in TNE was mostly due to an acquisition, and in 2007, after reducing TNE by 15%, ALU saw an increase in SE, but declines in OIE, OM, and OCFE.  This suggests that ALU may have cut profitable workers.

CorDell & Company recommends tracking these workforce productivity metrics as part of organizational performance management efforts to identify macro level changes in human capital productivity and to assess the impact of changes to human resources management practices within an organization.  For detailed information on how each of these organizations performs on these measures, request a copy of the research paper at http://www.cordellandcompany.com/hcpa_networkequipmfg.html.

For more insights into human capital visit http://executivesguide-humancapital.com.

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Method of Analysis

Using sales per employee (SE), operating income per employee (OIE), operating margin (OM), and total number of employees (TNE) we can analyze and quantify the productivity of an organization’s human capital.  To measure SE we divide annual revenues by TNE, and to measure OIE we divide annual operating income by TNE.  To measure OM we divide annual operating income by annual revenue.  All data is collected from annual and quarterly securities filings.  When comparing two or more organizations with fiscal years that end at different times of the calendar year we adjust comparisons to compare as many of the same calendar months as possible.  The equations for this analysis are as follows;

• Annual Revenues / TNE = SE
• Annual Operating Income / TNE = OIE
• Annual Operating Income / Annual Revenues = OM

Results

The average SE for all companies included in this study was $258,883.  ArvinMeritor (ARM) had the highest average SE at $334,358.  The average SE for Magna International (MGA) Denso Corporation (DNZOY), Autoliv (ALV), and TRW Automotive (TRW) was $287,175, $277,245, $181,400, and $214,239 respectively.  ARM’s SE increased about $5,000 from 2005 to 2009, while DNZOY’s SE increased about $16,000, TRW’s SE increased about $2,000, and both MGA and ALV saw a decrease in SE.  ARM’s human capital was clearly the most productive at generating top line revenues during this period, but DNZOY’s human capital made the most improvement in this area.

The average OIE for all companies included in this study was $7,741, which is negatively skewed due to the economic downturn in the automotive industry during 2008 and 2009.  DNZOY had the highest average OIE at $17,673, while MGA, ALV, ARM, and TRW had an average OIE of $6,403, $11,024, -$1,523, and $5,129 respectively.  DNZOY is the only company that made three consecutive year over year improvements in OIE, but TRW is the only company that improved OIE between 2008 and 2009.  Of particular note here is ARM, which had the highest average SE and the lowest average OIE.  While this might suggest ARM has very inefficient human capital, it might also reflect the nature of producing ARM’s specific mix of products.  Also important to note is ALV, which had the lowest average SE and the second highest average OIE.  This is quite an accomplishment when you consider that ALV’s average SE is 30% below the all company average SE.

The average OM for all the companies include in this study was 3.27%, again negatively skewed because of the economic downturn.  DNZOY had the highest average OM at 6.25%, while MGA, ALV, ARM, and TRW had an OM of 2.05%, 6.03%, -.57%, and 2.56% respectively.  The biggest surprise was that TRW was able to improve OM in 2009 from 2008 levels, however TRM did have the lowest OM in 2008 so one might argue they had nowhere to go but up.  TRW did have the best OM of all the companies included in this study in 2009, but it appears the economic downturn affected TRW more and earlier than these other companies and because of this TRW may have been more prepared for the economic conditions in 2009.  DNZOY saw the biggest drop in OM, from 2008 to 2009, but this is likely because DNZOY had the best average OM among these companies before 2009.

The average TNE for all the companies include in this study was 61,888.  DNZOY had the largest workforce with an average TNE of 112,188, and MGA, ALV, ARM, and TRW had an average TNE of 79,310, 33,860, 21,500, and 62,580 respectively.  What is surprising about this is that DNZOY, which has the largest workforce among this group of companies, is the only one of these companies to increase TNE every year!  While this is probably at least partially to blame for DNZOY’s large drops in OIE and OM in 2009, and may forecast workforce reductions in 2010, it might be a good strategic move if DNZOY is able to add higher performing talent than it already has, especially if the demand for automotive parts rebounds quickly.  The fact that DNZOY improved SE, OIE, and OM while increasing TNE before 2009 suggests the company knows how to hire more productive workers, improve the performance of its existing workers, or both and its continued increase in TNE during the economic downturn may be a strategic move to capitalize on an economic recovery.

Conclusion

Between 2005 and 2009 ARM’s human capital generated the most in top line revenues, but DNZOY’s human capital produced the most operating profits.  DNZOY also had the best average OM and was the only company to grow its TNE every year of this study.  This is why we believe DNZOY is the winning the ‘war for talent’ in the automotive parts industry.  DNZOY also appears to be winning the war for investors as its stock is up around 18% during this period.  TRW’s stock was up around 15%, which is likely due to its improved performance in 2009, while MGA, ALV, and ARM’s stocks were down around 39%, 10%, and 50% respectively.

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METHOD OF ANALYSIS

Using sales per employee (SE), operating income per employee (OIE), operating margin (OM), and total number of employees (TNE) we can analyze and quantify the productivity of an organization’s human capital.  To measure SE we divide annual revenues by TNE, and to measure OIE we divide annual operating income by TNE.  To measure OM we divide annual operating income by annual revenue.  All data is collected from annual and quarterly securities filings.  When comparing two or more organizations with fiscal years that end at different times of the calendar year we adjust comparisons to compare as many of the same calendar months as possible.  The equations for this analysis are as follows;

• Annual Revenues / TNE = SE
• Annual Operating Income / TNE = OIE
• Annual Operating Income / Annual Revenues = OM

RESULTS

The average SE for all companies included in this study was $150,894.  Omnicom Group Inc. (OMC) had the highest average SE at $179,556.  The average SE for Interpublic Group of Companies Inc. (IPG), WPP Group plc (WPP), and Publicis Groupe (PUB) was $150,231, $131,176, and $142,615 respectively.  OMC, which had the only average SE above the all company average SE, clearly has the most productive human capital when it comes to top line revenues.  Noteworthy is OMC’s significant upward trend in SE between 2007 and 2008.  Unfortunately OMC’s 2009 annual filing was not available at the time of this analysis, however its SE would have to decrease more than 75% in 2009 for its average SE to drop below its next closest competitor.  Also noteworthy is OMC’s almost 20% price premium, which implies that buyers of its services believe OMC generates 20% or more value than its competitors, and WPP’s downward trending SE from 2007 to 2008 while all other firms were still trending upwards.

The average OIE for all companies included in this study was $17,089.  OMC had the highest average OIE at $23,158, but this is a little misleading as OMC’s average does not include its OIE for fiscal year 2009.  As you can see from the graph above, PUB’s OIE was virtually equal to OMC’s OIE between fiscal years 2005 and 2008.  This is significant because PUB’s average SE was around 20% below OMC’s SE, but PUB’s average OIE was around 4% below OMC’s OIE.  OMC’s human capital appears to be the most productive when it comes to generating operating income, but it should be noted that PUB’s human capital is about as productive when it comes to generating operating income and PUB generates significantly less is top line revenues.  Also notable is the downward trend for WPP from 2007 to 2008 when all other firms were still trending upward.

The average OM for all the companies include in this study was 11.23%.  PUB had the highest average OM at 15.47%, which is about 19% higher than the next closest competitor.  This is expected given PUB’s average OIE is one of the highest while PUB’s average SE is one of the lowest, and it underscores just how efficient PUB’s human capital is at producing operating income.  While OMC’s human capital produced more in absolute operating income on average, on a relative basis PUB’s human capital is clearly more productive and this is reflected in PUB’s high OM.

The average TNE for all the companies include in this study was 60,898.  WPP’s average TNE was the highest at 92,118.  IPG, OMC, and PUB had an average TNE of 42,600, 66,500, and 42,375 respectively.  IPG was the only company to have a downward trending TNE, which might explain why IPG is the only firm to have an upward trending SE, OIE, and OM during this period.  This suggests IPG eliminated lower performing human capital assets during this period.  It is worth noting the significant growth in TNE by WPP, which is probably due to WPP’s continued acquisitions of other marketing and advertising agencies.  Also noteworthy is PUB’s TNE, which increased each of the five years included in this study.  This is noteworthy because PUB also has the best average OM and nearly the best average OIE, which suggests PUB is doing a good job of improving the productivity of its current human capital, adding more productive human capital, or both over time.

CONCLUSION

While OMC’s human capital was the most productive when it comes to generating revenues, its human capital produces about the same as PUB’s human capital in absolute terms when it comes to generating operating income.  Because PUB’s human capital is able to produce about the same in operating income as OMC while simultaneously producing 20% less in revenues we declare PUB the winner in the ‘war for talent’ among leading advertising agencies.  Not only did PUB’s human capital outperform its competitors human capital, but PUB’s stock did as well.  As you can see from the graph below (courtesy of Google Finance), PUB’s stock was up 19.5% over this time, while WPP’s stock was up 5.37% and OMC and IPG’s stock was down 7.13% and 44.92% respectively.

To request a PDF of this research article visit http://www.cordellandcompany.com/hcpa_adagencies.html.

For more insights into human capital visit the Executive’s Guide to Human Capital Blog.

To learn more about our founder CorDell Larkin visit his LinkedIn Profile.

To learn more about CorDell & Company’s services visit our website.

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METHOD OF ANALYSIS

Using sales per employee (SE), operating income per employee (OIE), operating margin (OM), and total number of employees (TNE) we can analyze and quantify the productivity of an organization’s human capital in financial terms.  To measure SE we divide annual revenues by TNE, and to measure OIE we divide annual operating income by TNE.  To measure OM we divide annual operating income by annual revenue.  All data is collected from an organization’s 10-K, 20-F, or other annual and quarterly securities filings.  When comparing two or more organizations with fiscal years that end at different times of the calendar year we will adjust comparisons to compare as many of the same calendar months as possible.  The equations for this analysis are as follows;

• Annual Revenues / TNE = SE
• Annual Operating Income / TNE = OIE
• Annual Operating Income / Annual Revenues = OM

RESULTS

The average SE for all companies included in this study was $656,621.  Dow Chemical (DOW) had the highest average SE at $1,103,920, which is 68% above the all company average.  DOW clearly has the most productive human capital among this group of companies when it comes to generating top line revenue.  However, DOW also saw the largest reduction in SE over this period with a drop of around 21%.  BASF (BAS) and DuPont’s (DD) SE was about the same in 2009 as it was in 2005.  Akzo Nobel (AKZA) increased SE around 26% over this five year period.

The wide variance seen in the graph of BAS and DOW’s SE is noteworthy.  Wide swings in SE such as this can be caused by a number of things.  In this case, we believe these changes are most likely the result of BAS and DOW’s inability to realign human capital and other assets to meet the markets demand for their products as fast as the market demand for those products changes.

The average OIE for all companies included in this study was $59,733.  BAS had the highest average OIE at $85,742, which is a bit of a surprise given BAS’ average SE was about 31% lower than DOW’s average SE.  BAS clearly had the most productive human capital during this period in terms of generating operating profits.  However, it should be noted that each of these companies have a downward trending OIE.  In fact, there are only three instances where any company had a year over year improvement in OIE and surprisingly AKZA’s improvement in OIE came between 2008 and 2009.  This suggests AKZA is the only firm to have improved its human capital productivity this past year.  Additionally, AKZA had the lowest decrease in OIE during this five year period with a drop of about 30%.

The average OM for all the companies include in this study was 9.31%.  BAS had the highest average OM at 11.34%.  This is somewhat expected given BAS had the highest average OIE without having the highest average SE, and shows that BAS’ human capital is the most productive even with less resources than some of its competitors.  Again we see that in only three instances did one of these firms make an improvement on this measure, and surprisingly two instances occurred this past year with both AKZA and DD improving OM in 2009.  DD enjoyed the lowest drop in OM during this period with a drop of about 37%.  AKZA had the best year over year improvement in OM, surprisingly this was in 2009 and was also the best year over year improvement of any of these companies at any time in this study.  This suggests AKZA may be able to match its human capital assets to demand for its products better than the other companies included in this study.

The average TNE for all the companies include in this study was 65,066.  BAS had the largest workforce with an average of 94,614 employees.  Of particular interest is the growth in TNE by both DOW and BAS given the recent economic downturn.  Given BAS has the largest workforce, the highest average OIE, and downward trending SE, OIE, and OM this might suggest BAS has the lions share of high quality talent in this industry.  If this is the case then BAS should invest more in efforts to retain and develop its current talent, and competitors may want to look at better ways to poach BAS employees.  DOW’s growth in TNE is largely due to acquiring Rohm and Haas, and given its consistently downward trending SE, OIE, and OM may be cause for concern about its ability to realize expected synergies from integration.

AKZA and DD both decreased the size of their workforce during this period, although not significantly.  With their recent improvements in OIE and OM this might suggest they are doing a good job of identifying redundant and lower performing human capital assets and eliminating them.  However, caution should be taken when eliminating human capital assets that produce more than the cost of capital necessary to employ and manage them.  Yet small changes in TNE relative to larger positive changes in SE, OIE, and OM tend to suggest good human capital management practices.

CONCLUSION

Identifying the company that is winning the war for the “most productive” talent is not so easy in this case.  On average DOW had the best performing human capital when it comes to top line productivity, but AKZA’s human capital is improving the fastest in this area.  On average BAS had the best performing human capital when it comes to generating operating profits, but AKZA is the only one making improvements in this area.  BAS has the largest workforce and is growing the fastest, but its human capital appears to be less productive as time goes on.  AKZA’s human capital appears to become more productive over time, but the company is decreasing and not increasing the size of its workforce.  Because of its absolute level of productivity, we believe BAS’ human capital is the best in the chemical manufacturing industry.   Yet we must give recognition to AKZA for being the only company among this group that appears to be improving the productivity of its human capital, and it appears we are not the only ones that feel this way.  One glance at the chart below (Courtesy of Google Finance) and you will see that investors recognize AKZA as well.  AKZA’s stock increased 47% during this period, while BAS, DOW, and DD declined 18%, 43%, and 31% respectively.

To request a PDF of the article, including raw data, visit Human Capital Productivity Analysis for Chemical Manufacturers.

For more insights into human capital visit the Executive’s Guide to Human Capital Blog.

To learn more about our founder CorDell Larkin visit his LinkedIn Profile.

To learn more about CorDell & Company’s services visit our website.

Follow CorDell & Company on Twitter.

METHOD OF ANALYSIS

Using sales per employee (SE), operating income per employee (OIE), operating margin (OM), and total number of employees (TNE) we can quantify the productivity of an organization’s human capital in financial terms.  To measure SE we divide annual revenues by TNE, and to measure OIE we divide annual operating income by TNE.  To measure OM we divide annual operating income by annual revenue.  All data is collected from the organization’s 10-K or 20-F.  When comparing two or more organizations who’s fiscal years end at different times of the calendar year we will adjust comparisons to compare as many of the same calendar months as possible.  For example, an organization that ended its 2009 fiscal year in March of 2009 may have its 2009 fiscal year compared to another organization’s 2008 fiscal year if the other organization’s 2008 fiscal year ended December of 2008.  The equations for this analysis are as follows;

1. Annual Revenues / TNE = SE
2. Annual Operating Income / TNE = OIE
3. Annual Operating Income / Annual Revenues = OM

RESULTS

The average SE for all companies included in this study was $396,940.  CNH Global N.V. (CNH) had the highest average SE at $540,872 while Joy Global Inc. (JOYG) had the lowest average SE at $279,779.  Because it produced about 36% more in SE than the average for all these companies, and about 15% more in SE than its next closest competitor, CNH wins the war for talent when it comes to top line productivity.  However, JOYG was the only company to improve SE every year of this study, and JOYG, The Manitowoc Company Inc. (MTW), and Bucyrus International, Inc. (BUCY) were the only companies to have higher SE in 2009 than 2005.  Caterpillar Inc. (CAT) and Terex Corporation (TEX) both had significantly lower SE in 2009 than in 2005, and Deere & Company’s (DE) SE remained relatively steady during this time.

The average OIE for all companies included in this study was $37,966.  JOYG had the highest average OIE at $48,754 while CNH had the lowest average OIE at $23,209.  This is surprising given that these two companies held the exact opposite positions when comparing SE.  Because it produced roughly 28% more OIE than the average for all these companies and about 7% more in OIE than its next closest competitor, while producing the least in SE, JOYG clearly has the most productive human capital among this group of companies.  However, it should be noted that both JOYG and BUCY improved OIE from 2005 to 2009 and that in 2008 and 2009 BUCY had a higher OIE than JOYG.  DE, MTW, CNH, CAT, and TEX all had significant declines in OIE from 2005 to 2009.

The average OM for all the companies include in this study was about 10%.  JOYG had the highest average OM at 17.3%, which is expected given they have the highest OIE, and CNH had the lowest average OM at 4.18%.  As with OIE, JOYG and BUCY are the only two firms that improved OM from 2005 to 2009.  While all the other firms’ OM dropped significantly in 2009, it should be noted that CNH’s OM was improving before this.

The average TNE for all the companies include in this study was 31,805.  CAT had the largest workforce with an average TNE of 98,482 and BUCY had the smallest workforce with an average TNE of 4,935.  Six of the seven companies included in this study increased TNE from 2005 to 2009, even though all of these companies reduced TNE from 2008 to 2009.  However, both JOYG and BUCY reduced TNE by less than .5% from 2008 to 2009, which is amazing given the depth of the recession.  Even more impressive is that fact that BUCY increased its TNE almost 325% from 2005 to 2009, all while increasing its SE, OIE, and OM.

CONCLUSION

Between 2005 and 2009 CNH’s human capital produced the most in top line sales, JOYG’s human capital generated the highest OIE and OM, and BUCY’s human capital grew the fastest.  Because JOYG had the highest average OIE and OM, while having the lowest average SE, of all these companies, we declare JOYG has the best human capital among heavy equipment manufacturers.  As you can see below, investors have rewarded JOYG for  the performance of its human capital.  JOYG’s stock is up 166.9% from 2005 to 2009.  However, BUCY’s stock is up 315.91% from 2005 to 2009.  Why is this?  While it is difficult to say definitively why investors have rewarded BUCY more than JOYG, this analysis does offer some plausible explanations.  BUCY’s average SE was higher than JOYG, so if investors believe BUCY’s human capital will become as efficient at producing profits as JOYG’s human capital then BUCY’s absolute operating profits would become larger than JOYG’s operating profits making its stock more valuable.  In 2008 and 2009 we can see this is exactly what happened as BUCY’s OIE surpassed JOYG’s OIE.  Of course, there are other plausible reasons for BUCY’s stock increasing so rapidly in late 2009.  BUCY did announce a takeover of TEX’s mining business, and takeovers have a way of exciting investors.  If BUCY is able to instill the same level of human capital productivity in TEX’s mining business that it has in its other businesses investor excitement over this deal is probably well deserved.

To request a PDF of this research report visit http://bit.ly/cyYUAL.

For more insights into human capital visit the Executive’s Guide to Human Capital Blog.

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Several studies have shown the number one reason employees leave their job is their immediate supervisor.  If an employee has issues with their immediate supervisor can we really expect that supervisor to know the real answers to the questions Mr. Finnegan poses in his article?  Less than 10% of the executives I’ve provided consulting services to would give their boss candid feedback about their “areas for development” unless it was anonymous feedback, which is why we have 360 or multirater surveys.  If this ratio is true for all employees in every organization than the supervisor’s manager could expect accurate data on why an employee left about 10% of the time.  I hope no organization is making decisions about how to improve employee retention with such a low level of data accuracy.

Mr. Finnegan recognizes the logic behind the exit interview approach to identifying the reasons people leave, but admits that this strategy is flawed for several reasons.  He even adds that when surveyed 90% of HR managers say they do exit interviews but only 10% say their company is improved with the data they collect from them.

I understand the urge to hold supervisors accountable for retention because they should be.  However, I think the best way to do this is to reward them for it.  Make retention part of a company’s rewards programs and I’m sure you will see a change in supervisor behavior, and not just in how they treat employees but how they select them as well.  Until this is done you are committing Steven Kerr’s “Folly of Rewarding A, While Hoping for B.”  You can purchase a copy of this timeless management article at http://www.jstor.org/pss/255378.  It is still a good read.

In my experience, once an employee decides to leave you have already missed the opportunity to get honest feedback about why they chose to take another career opportunity.  Only when an employee is engaged and still interested in making something out of the opportunity they have can you get real, candid feedback about what they like and don’t like because they are motivated to improve upon the situation. Once an employee has given up hope of improving the situation in their current position I believe you are better off waiting until a little while after they have made a change to ask them why they left, and I recommend you do it through a trusted friend or an objective third party.  This will improve the accuracy of the data and show the former employee you are serious about making changes.  It will also go a long way towards making that former employee consider coming back to work for your organization in the future should you want them to.

Read Mr. Finnegan’s article at http://bit.ly/cYn9rP.

For more insights into human capital visit the Executive’s Guide to Human Capital Blog.

To learn more about author CorDell Larkin visit his LinkedIn Profile.

To learn more about CorDell & Company’s services visit our website.

Follow CorDell & Company on Twitter.